Austin Esparza

About Austin Esparza

Genetic testing explains far less about disease than the volume of sequencing data would…

Experience

1. U-grow Scholar

   Cedars-Sinai

   May 2025 — Present · West Hollywood, CA, US

   Under the guidance of Nimisha Mazumdar in Michelle Jones’ lab, I contributed to workflows for germline variant interpretation in epithelial ovarian cancer. The project focused on two complementary analyses using public databases and case-control datasets to better characterize genetic risk in known genes such as BRCA1 and BRCA2.Aim 1: Structural Variants (SVs). Based on the hypothesis that germline SVs confer risk for ovarian cancer, I used DRAGEN-called whole-genome sequencing data to quantify deletions, duplications, inversions, and breakends across cases and controls. Normalization by chromosome length showed that deletions covered more of the genome than duplications in both cohorts, and case burden was highest on a subset of large chromosomes.Aim 2: Pathogenic SNPs and Indels. Using ClinVar and dbSNP, I identified pathogenic variants represented on Illumina’s Global Diversity Array. Results showed that BRCA1/2 accounted for ~98% of array-detectable pathogenic sites, with PALB2 as the leading non-BRCA gene. In two case cohorts, 21-26% of individuals carried a pathogenic variant, which enabled classification of BRCA(+) and BRCA(-) carriers and nomination of non-carriers for risk SV discovery.This work produced curated variant tables, normalized burden plots, and a documented codebase, contributing infrastructure that supports ongoing efforts to map ovarian cancer genetic risk and improve variant visibility in diverse populations.

Education

• California State University, Long Beach

  Bachelor of Science - BS

• University of Nevada-Reno

  Molecular Microbiology and Immunology

  2014 — 2018